Note: The following post is a recap generated with Copy.ai. The goal was to summarize the main points of the full-length interview in a quick and digestible form. That said, we highly encourage you to watch the full video and connect with Shyam on LinkedIn.
Artificial intelligence is rapidly transforming content creation and strategy. New AI tools promise to help generate higher quality content at scale, automate tedious writing tasks, and provide creative inspiration on demand.
However, these tools fall short without proper implementation and oversight.
In this interview, Shyam shares his guidance on setting realistic expectations, prompting properly, and focusing on people first when implementing AI for content creation. By following his expert advice, brands can harness AI as an amplifier rather than a crutch when enhancing their content strategy.
Let’s dive in!
Many people have unrealistic expectations for AI. They view it as a magic wand that will automatically generate high-quality content if you simply plug it in.
But AI is not magic - it requires careful implementation to see results.
As Shyam notes, AI should be viewed as a means to an end, not the end goal itself. It exists to support people and processes, not replace them.
One of the biggest places where AI initiatives often fail is when people expect AI to instantly solve all their problems without supplying good data, context, training, and governance.
Shyam explains that proper implementation is the key to successfully leveraging AI. Like any tool, it requires expertise and effort to use AI effectively. You cannot simply plug it in and expect it to churn out Pulitzer-level prose.
Effective content still requires quality data inputs, well-defined objectives, and human guidance.
So set realistic expectations for AI up front.
Do not expect it to magically create high-quality content on its own. View it as a tool to aid people and enhance processes when implemented properly. With realistic expectations and an expert, thoughtful approach, AI can elevate content creation significantly.
But it is not a magic wand - again, success requires expertise and effort.
One of the most practical applications of generative AI is overcoming writer's block and enhancing creativity in content creation. With the right prompts and ample context supplied, AI can help generate conclusions to articles and craft catchy headlines and social media posts.
For example, if a writer is stuck trying to come up with a compelling headline, they can provide the AI with the core theme or angle of the piece, key information that needs to be conveyed, target length, and tone. Then, the right AI tool can rapidly generate multiple headline options within seconds for the writer to choose from.
Similarly, if a writer has completed the body of an article but is struggling with the conclusion, they can provide the AI with the key points covered and the main takeaway. The AI can suggest effective ways to wrap up the piece and drive home the main message.
Generative AI is also great for instantly creating draft social media posts, particularly for platforms like LinkedIn where concise expression is key. When provided with the right prompts indicating the core message, target audience, and desired tone, the AI can produce catchy snippets of text that capture attention.
The key is supplying the AI with enough contextual information so that it can understand the core objective and produce relevant results.
Well-framed prompts are critical to getting quality output from generative AI tools. With practice, writers can learn how to provide the AI with just enough direction to spark creativity without overly constraining it.
Used properly, generative AI has enormous potential to become a writer's creative partner - helping tackle writer's block, craft compelling headlines and summaries, and enhance overall content quality. It enables writers to tap into an artificial brain trust, quickly exploring more ideas than would be possible solo.
This can take content creation to new levels.
When implementing AI, it's important not to get caught up in the technology alone. The people and processes supporting the AI are just as critical to success.
As Shyam notes, data issues are a fundamental challenge across industries. If the data being supplied to the AI is incomplete, biased, or of poor quality, it will produce poor results.
Garbage in, garbage out.
He also emphasizes that AI success is really about people and processes first, then technology.
The most advanced AI system will fail if the surrounding workflows, infrastructure, and personnel are not equipped to support it. Proper implementation requires investing in processes to clean, structure, and supply data.
The key takeaway here is that AI fails when people don't supply good data.
Data hygiene and management may not be glamorous, but they provide the foundation for AI. In addition to data, Shyam stresses the importance of people in ensuring AI lives up to its promise.
With realistic expectations and by focusing on people and processes first, leaders can successfully leverage AI to enhance their content strategy.
As we have seen, properly leveraging AI to enhance your content strategy requires setting realistic expectations upfront. AI is a tool that can help generate initial ideas and drafts but still requires human creativity, expertise and oversight.
When implemented correctly, generative AI can help overcome writer's block, craft creative headlines and posts, and expand your content capabilities.
However, simply plugging AI into your content process will not magically create high-quality, strategic content on its own.
The key factors for success with AI remain focusing on people, processes, data quality and proper prompting first. Having clear goals, quality data inputs, and thoughtful guidance of the AI will determine if it succeeds or fails. With the right approach, content teams can use AI as an asset while maintaining human strategic oversight over the final output.
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